PRODUCT PLACEMENT IN RETAIL SETTINGS

• US 20130339083A1
• Filed: 06/13/2012
• Published: 12/19/2013
• Est. Priority Date: 06/13/2012
• Status: Abandoned Application

• Current Assignee: Target Brands Inc. (Target Corporation)
• Original Assignee: Target Brands Inc. (Target Corporation)
• Inventors: Baier, Mark Walter, Kaur, Harpreet, TE, Sriram, Storrs, Kristin Anne, Simmons, Alyssa Donna
• Application Number:
  US13/495,968
• Publication Number:
  US 20130339083A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Products are selected for placement on check-out lane end caps at retail store locations. In one example, products are selected for placement on check-out lane end caps in one or more stores based on historical sales data for each product across all of the stores. Each check-out lane end cap includes a fixture configured to hold and display product(s) for sale in a store. A total number of stores into which each product is to be placed in at least one check-out lane end cap is received. A sales performance metric is determined for each selected product based on in-store historical sales data representative of sales of the product in each store. A particular store into which to place each selected product in a check-out lane end cap is determined based on the received total number of stores and the determined sales performance metric for the product.

Claims

1. A method comprising:

selecting a plurality of products from a larger plurality of products, the selected plurality of products being a subset of the larger plurality of products, and the selected plurality of products to be placed in a plurality of check-out lane end caps in a plurality of stores based at least in part on historical sales data for each of the plurality of products across all of the plurality of stores, wherein each of the plurality of check-out lane end caps comprises a fixture configured to hold and display one or more products for sale in a store;

receiving a total number of stores into which each of the selected products is to be placed in at least one check-out lane end cap;

receiving at least one bid associated with a product of the larger plurality of products, wherein the at least one bid comprises a request to place the product in at least one of the plurality of check-out lane end caps, and at least one of a cost price of an inventory of the product an inventory amount of the product a turnaround time associated with replenishing inventory of the product, and a total number of stores into which the product is to be placed;

determining, with a computing device, a sales performance metric for each of the selected products based at least in part on in-store historical sales data representative of sales of the product in each of the plurality of stores; and

determining, with the computing device, which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the received bid, and the determined sales performance metric for the product.

2. The method of claim 1, wherein each of the plurality of check-out lane end caps in each of the plurality of stores comprises a level of priority selected from a plurality of levels of priority in a predetermined order, the method further comprising:

assigning each of the selected products a priority level that corresponds to one of the plurality of levels of priority of the check-out lane end caps; and

determining, with the computing device, which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the determined sales performance metric for the product, and the assigned priority level of the product.

3. The method of claim 2, wherein the plurality of stores is categorized into groups, wherein each group of stores is associated with a store classification, and further comprising:

assigning a first selected product of the selected products to a first store classification of the store classifications; and

allocating the first selected product to only those groups of stores that have the first store classification, and that include a check-out lane end cap with a level of priority that is equal to the priority level assigned to the first selected product.

4. The method of claim 3, further comprising:

assigning a second selected product of the selected products to a second store classification of the store classifications; and

allocating the second selected product to only those groups of stores that have the second store classification, and that include a check-out lane end cap with a level of priority that is equal to the priority level assigned to the second selected product,

wherein the priority level of the first selected product is equal to the priority level of the second selected product.

7. The method of claim 1, wherein each of the plurality of check-out lane end caps in each of the plurality of stores comprises a level of priority selected from a plurality of levels of priority in a predetermined order, and wherein the bid comprises a priority level for the product that corresponds to one of the plurality of levels of priority of the check-out lane end caps.

8. The method of claim 1, further comprising:

selecting a time period during which to place products in the plurality of check-out lane end caps in the plurality of stores,

wherein at least one of selecting the plurality of products to be placed in the plurality of check-out lane end caps and determining, with the computing device, which of the plurality of stores to place each product in a check-out lane end cap of that store is based at least in part on the selected time period.

9. The method of claim 1, further comprising:

designating one of the plurality of stores as a new store;

comparing at least one characteristic of the new store to a corresponding characteristic of one or more other stores of the plurality of stores;

based on the comparison, designating at least one of the one or more other stores as a model store for the new store; and

employing in-store historical sales data representative of sales of each of the plurality of products in the model store as in-store historical sales data representative of sales of each of the plurality of products in the new store.

10. The method of claim 1, further comprising:

normalizing the historical sales data for each of the plurality for each of the selected products across all of the plurality of stores, by at least one of scaling the historical sales data based on a sales volume associated with each of the plurality of stores, determining a percentage of total sales at each of the plurality of stores represented by the historical sales data of each of the selected products, and comparing the historical sales data of each of the selected products to a chain average associated with each of the selected products, wherein the chain average represents an average value of sales of each of the selected products across all of the plurality of stores.

11. The method of claim 1, wherein the selected products to be placed in the plurality of check-out lane end caps is a first plurality of products, and wherein selecting the first plurality of products to be placed in the plurality of check-out lane end caps further comprises:

identifying a second plurality of products larger than the first plurality of products, wherein the second plurality of products includes all products of the first plurality of products and at least one product not included in the first plurality of products, and wherein each product of the second plurality of products comprises a product categorized as an impulse purchase product; and

selecting the first plurality of products from the second plurality of products.

12. The method of claim 1, further comprising:

receiving a unit price for each of the selected plurality of products; and

determining, with the computing device, which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the determined sales performance metric for the product, and the unit price for the product.

13. The method of claim 1, wherein the sales performance metric determined for each of the selected products comprises at least one of sales revenue, profit, or sales volume for each product.

5. -6. (canceled)

14. A device comprising:

a memory; and

at least one programmable processor configured to execute one or more instructions stored to the memory to perform operations comprising;

selecting a plurality of products from a larger plurality of products, the selected plurality of products being a subset of the larger plurality of products, and the selected plurality of products to be placed in a plurality of check-out lane end caps in a plurality of stores based at least in part on historical sales data for each of the plurality of products across all of the plurality of stores, wherein each of the plurality of check-out lane end caps comprises a fixture configured to hold and display one or more products for sale in a store;

receiving a total number of stores into which each of the selected products is to be placed in at least one check-out lane end cap;

receiving at least one bid associated with a product of the larger plurality of products, wherein the at least one bid comprises a request to place the product in at least one of the plurality of check-out lane end caps, and at least one of a cost price of an inventory of the product, an inventory amount of the product, a turnaround time associated with replenishing inventory of the product, and a total number of stores into which the product is to be placed;

determining a sales performance metric for each of the selected products based at least in part on in-store historical sales data representative of sales of the product in each of the plurality of stores; and

determining which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the received bid, and the determined sales performance metric for the product.

15. The device of claim 14, wherein each of the plurality of check-out lane end caps in each of the plurality of stores comprises a level of priority selected from a plurality of levels of priority in a predetermined order, and wherein the at least one programmable processor is configured to perform operations further comprising:

assigning each of the selected products a priority level that corresponds to one of the plurality of levels of priority of the check-out lane end caps; and

determining, with the computing device, which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the determined sales performance metric for the product, and the assigned priority level of the product.

16. The device of claim 15, wherein the at least one programmable processor is configured to perform operations further comprising:

assigning a first selected product of the selected products to a first store classification of the store classifications; and

allocating the first selected product to only those groups of stores that have the first store classification, and that include a check-out lane end cap with a level of priority that is equal to the priority level assigned to the first selected product.

17. The device of claim 16, wherein the at least one programmable processor is configured to perform operations further comprising:

assigning a second selected product of the selected products to a second store classification of the store classifications; and

allocating the second selected product to only those groups of stores that have the second store classification, and that include a check-out lane end cap with a level of priority that is equal to the priority level assigned to the second selected product,

wherein the priority level of the first selected product is equal to the priority level of the second selected product.

20. The device of claim 14, wherein each of the plurality of check-out lane end caps in each of the plurality of stores comprises a level of priority selected from a plurality of levels of priority in a predetermined order, and wherein the bid comprises a priority level for the product that corresponds to one of the plurality of levels of priority of the check-out lane end caps.

21. The device of claim 14, wherein the at least one programmable processor is configured to perform operations further comprising:

selecting a time period during which to place products in the plurality of check-out lane end caps in the plurality of stores,

wherein at least one of selecting the plurality of products to be placed in the plurality of check-out lane end caps and determining, with the computing device, which of the plurality of stores to place each product in a check-out lane end cap of that store is based at least in part on the selected time period.

22. The device of claim 14, wherein the at least one programmable processor is configured to perform operations further comprising:

designating one of the plurality of stores as a new store;

comparing at least one characteristic of the new store to a corresponding characteristic of one or more other stores of the plurality of stores;

based on the comparison, designating at least one of the one or more other stores as a model store for the new store; and

employing in-store historical sales data representative of sales of each of the plurality of products in the model store as in-store historical sales data representative of sales of each of the plurality of products in the new store.

23. The device of claim 14, wherein the at least one programmable processor is configured to perform operations further comprising:

normalizing the historical sales data for each of the plurality for each of the selected products across all of the plurality of stores, by at least one of scaling the historical sales data based on a sales volume associated with each of the plurality of stores, determining a percentage of total sales at each of the plurality of stores represented by the historical sales data of each of the selected products, and comparing the historical sales data of each of the selected products to a chain average associated with each of the selected products, wherein the chain average represents an average value of sales of each of the selected products across all of the plurality of stores.

24. The device of claim 14, wherein the at least one programmable processor is configured to perform operations further comprising:

receiving a unit price for each of the selected plurality of products; and

determining, with the computing device, which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the determined sales performance metric for the product, and the unit price for the product.

25. The device of claim 14, wherein the sales performance metric determined for each of the selected products comprises at least one of sales revenue, profit, or sales volume for each product.

18. -19. (canceled)

26. A computer-readable storage device encoded with instructions that, when executed, cause one or more processors of a computing device to:

select a plurality of products from a larger plurality of products, the selected plurality of products being a subset of the larger plurality of products, and the selected plurality of products to be placed in a plurality of check-out lane end caps in a plurality of stores based at least in part on historical sales data for each of the plurality of products across all of the plurality of stores, wherein each of the plurality of check-out lane end caps comprises a fixture configured to hold and display one or more products for sale in a store;

receive a total number of stores into which each of the selected products is to be placed in at least one check-out lane end cap;

receive at least one bid associated with a product of the larger plurality of products, wherein the at least one bid comprises a request to place the product in at least one of the plurality of check-out lane end caps, and at least one of a cost price of an inventory of the product an inventory amount of the product, a turnaround time associated with replenishing inventory of the product, and a total number of stores into which the product is to be placed;

determine a sales performance metric for each of the selected products based at least in part on in-store historical sales data representative of sales of the product in each of the plurality of stores; and

determine which of the plurality of stores to place each of the selected products in a check-out lane end cap of that store based at least in part on the received total number of stores into which the product is to be placed, the received bid, and the determined sales performance metric for the product.